code: def test_classifier_uncertainty(cu_params):
      preds_type, uncertainty_type = cu_params
      clf = LogisticRegression().fit(X_train, y_train_clf)
      model_fn = (
          clf.predict_log_proba
          if preds_type == "logits"
          else clf.predict_proba
      )
      uncertainties = classifier_uncertainty(
          X_test,
          model_fn,
          preds_type=preds_type,
          uncertainty_type=uncertainty_type,
      )
      assert uncertainties.shape == (X_test.shape[0], 1)
  
file_path: alibi-detect/alibi_detect/cd/tests/test_preprocess.py
imports: from itertools import product
  import numpy
  import pytest
  import torch.nn
  import torch
  from sklearn.linear_model import LogisticRegression
  from alibi_detect.cd.preprocess import classifier_uncertainty, regressor_uncertainty
label_desc: Use image node_id 2 for calling a global function with example usage: test_classifier_uncertainty(cu_params) without return types